An interventional medical procedure is typically a minimally invasive procedure performed under image guidance. Common interventional imaging methods include X-ray fluoroscopy, computer tomography (CT), ultrasound (US), and magnetic resonance imaging (MRI). Examples of interventional procedures typically include balloon angioplasty, lesion biopsy, chemoembolization, radiofrequency ablation and drain insertions.
During many types of interventional procedures, the physician relies on information not visible in intra-operative images, but is available in pre-operative images. For example, a thoracic lesion that is the target of a biopsy procedure may not be easily visible on ultrasound or X-ray fluoroscopy used during the intervention. However, the same lesion may be visible on pre-procedural diagnostic CT images. Therefore, there is great need for bringing pre-operative images into the interventional procedure room and in integrating or fusing the information that they present with the intra-procedural images.
Unless the context suggests otherwise, the terms post-procedural and post-operative are used herein interchangeably. In many procedures, there is also a need to assess the outcome of the procedure via post-procedural images. For example, positron emission tomography (PET) images acquired after the intervention may provide the physician with information on the efficacy of the embolization of a liver tumor. Therefore, such post-procedural images may need to be fused with pre-operative and intra-operative images for effective comparison and collective examination of the information presented in all these images simultaneously.
In the above-mentioned circumstances, for which there is a need to combine information from pre-operative, intra-operative, and post-operative images, solutions proposed in the prior art typically decouple the image registration and fusion tasks from other pre-, intra-, and post-procedural tasks. Thus, for example, software tools are available for segmenting and computing the volume of a liver tumor based on a pre-procedural CT, but a separate tool is used for registration and fusion of the same pre-procedural CT image with intra-procedural CT or US image. The use of multiple software tools during a single medical procedure, and the decoupling of technically required steps from clinical tasks, provide for a suboptimal workflow in many interventional procedures. Moreover, solutions in the prior art are generally not able to transfer objects associated with one image, such as a planned needle trajectory or the contour of a segmented tumor, across different images belonging to the same patient, for comparison, or for use in guiding the interventional procedure.
Various aspects relating generally to the background and field of the present invention are treated in a number of text-books, in addition to the publications referred to in the course of the description of the present invention. For example, reference is made to the following text-books for background material which may be found useful: VIRTUAL ENDOSCOPY AND RELATED 3D TECHNIQUES, Editors P. Rogalla, J. Terwisscha van Schelting a, and B. Hamm, published by Springer, Berlin, N.Y., and London, 2001, 2002; MEDICAL IMAGE REGISTRATION, edited by Joseph B. Hajnal, Derek L. G. Hill, and David J. Hawkes in the Biomedical Engineering Series published by CRC Press, Boca Raton, London, New York and Washington, D.C., 2001; DIGITAL IMAGE PROCESSING, by Gonzalez and Woods, published by Prentice-Hall Inc., New Jersey, 2002; LEVEL SET METHODS AND FAST MARCHING METHODS, by J. A. Sethian, published by Cambridge University Press, 1996; 1999; IMAGE PROCESSING, ANALYSIS, AND MACHINE VISION, by Sonka, Hlavac, and Boyle, published by Brooks/Cole Publishing Company, Pacific Grove, Calif., 1999; INSIGHT INTO IMAGES, editor Terry S. Yoo, published by A K Peters, Wellesley Mass., 2004; and FUNDAMENTALS OF ELECTRONIC IMAGE PROCESSING, by A. R. Weeks, Jr., IEEE Press, New York, 1996; and various other text-books.